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      Natural mating ability is associated with gut microbiota composition and function in captive male giant pandas

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          Abstract

          The issue of poor sexual performance of some male giant pandas seriously impairs the growth and the genetic diversity of the captive population, yet there is still no clear understanding of the cause of the loss of this ability and its underlying mechanism. In this study, we analyzed the gut microbiota and its function in 72 fecal samples obtained from 20 captive male giant pandas, with an equal allocation between individuals capable and incapable of natural mating. Additionally, we investigated fecal hormone levels and behavioral differences between the two groups. A correlation analysis was then conducted among these factors to explore the influencing factors of their natural mating ability. The results showed significant differences in the composition of gut microbiota between the two groups of male pandas. The capable group had significantly higher abundance of Clostridium sensu stricto 1 ( p adjusted = .0021, GLMM), which was positively correlated with fatty acid degradation and two‐component system functions (Spearman, p adjusted < .05). Additionally, the capable group showed higher gene abundance in gut microbiota function including purine and pyrimidine metabolism and galactose metabolism, as well as pathways related to biological processes such as ribosome and homologous recombination (DEseq2, p adjusted < .05). We found no significant differences in fecal cortisol and testosterone levels between the two groups, and no difference was found in their behavior either. Our study provides a theoretical and practical basis for further studying the behavioral degradation mechanisms of giant pandas and other endangered mammal species.

          Abstract

          This study investigated the gut microbiota of captive male giant pandas and found significant differences between the microbiota of individuals’ capable and incapable of natural mating. The findings provide insight into potential mechanisms affecting the reproductive success of endangered mammal species.

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          DADA2: High resolution sample inference from Illumina amplicon data

          We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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            phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

            Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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              Welcome to the Tidyverse

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                Author and article information

                Contributors
                dzliu@bnu.edu.cn
                Journal
                Ecol Evol
                Ecol Evol
                10.1002/(ISSN)2045-7758
                ECE3
                Ecology and Evolution
                John Wiley and Sons Inc. (Hoboken )
                2045-7758
                01 April 2024
                April 2024
                : 14
                : 4 ( doiID: 10.1002/ece3.v14.4 )
                : e11189
                Affiliations
                [ 1 ] Department of Ecology, College of Life Sciences, Key Laboratory for Biodiversity and Ecological Engineering of Ministry of Education Beijing Normal University Beijing Hebei China
                [ 2 ] Research Center for the Qinling Giant Panda Shaanxi Rare Wildlife Rescue Base Xi'an Shaanxi China
                [ 3 ] China Conservation and Research Centre for the Giant Panda Wolong Sichuan China
                Author notes
                [*] [* ] Correspondence

                Dingzhen Liu, Department of Ecology, College of Life Sciences, Key Laboratory for Biodiversity and Ecological Engineering of Ministry of Education, Beijing Normal University, Beijing 100875, Hebei, China.

                Email: dzliu@ 123456bnu.edu.cn

                Author information
                https://orcid.org/0000-0003-1780-6134
                https://orcid.org/0000-0002-1870-6197
                Article
                ECE311189 ECE-2023-11-02001.R1
                10.1002/ece3.11189
                10985376
                38571808
                b36f995b-704a-4fa4-a4d2-fa3d658a3c0e
                © 2024 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 05 March 2024
                : 15 November 2023
                : 12 March 2024
                Page count
                Figures: 7, Tables: 0, Pages: 14, Words: 10613
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: Grant#32270506
                Award ID: 31772466
                Award ID: 31472009
                Funded by: National Forestry and Grassland Administration, P. R. China
                Award ID: 2019‐BJ018
                Categories
                Behavioural Ecology
                Biodiversity Ecology
                Conservation Ecology
                Microbial Ecology
                Microbiomics
                Research Article
                Research Articles
                Custom metadata
                2.0
                April 2024
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.4.0 mode:remove_FC converted:02.04.2024

                Evolutionary Biology
                behavior,breeding,genetic diversity,giant panda,gut microbiota,hormone
                Evolutionary Biology
                behavior, breeding, genetic diversity, giant panda, gut microbiota, hormone

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